By learning from cheaper or publicly accessible data, WSOD [1]}, [2]}, [3]} decreases its over-reliance on fine-grained labeling.
PCL [1]} builds proposal clusters iteratively to aid in the construction of instance classifiers.
Pseudo labels elicited from picture labels [2]} and unstructured textual descriptions such as captions [3]} are also useful for improving WSOD performance.
WSOD, on the other hand, often relies on a fixed-size collection of predefined classes and is thus unsuitable for our proposed task, since class labels are not available and categories may be changed dynamically.
